In this section, we describe the proposed MVS network referred to as CDS-MVSNet, which predicts a depth map \(D^{ref}\)  from the reference \(I^0\)  and \(N\)  source images \(\lbrace I_i\rbrace _{i=1}^N\) . We adopted the cascade structure of CasMVSNet [1]} as the baseline structure of CDS-MVSNet. The network is composed of multiple cascade stages to predict the depth maps in a coarse-to-fine manner. Each stage estimates a depth through three steps: feature extraction, cost volume formulation, cost volume regularization & depth regression.
